Metadata-Version: 2.1
Name: insightface
Version: 0.7.1
Summary: InsightFace Python Library
Home-page: https://github.com/deepinsight/insightface
Author: InsightFace Contributors
Author-email: contact@insightface.ai
License: MIT
Description: InsightFace Python Library
        ==========================
        
        License
        -------
        
        The code of InsightFace Python Library is released under the MIT
        License. There is no limitation for both academic and commercial usage.
        
        **The pretrained models we provided with this library are available for
        non-commercial research purposes only, including both auto-downloading
        models and manual-downloading models.**
        
        Install
        -------
        
        Install Inference Backend
        ~~~~~~~~~~~~~~~~~~~~~~~~~
        
        For ``insightface<=0.1.5``, we use MXNet as inference backend.
        
        Starting from insightface>=0.2, we use onnxruntime as inference backend.
        
        You have to install ``onnxruntime-gpu`` manually to enable GPU
        inference, or install ``onnxruntime`` to use CPU only inference.
        
        Change Log
        ----------
        
        [0.7.1] - 2022-12-14
        ~~~~~~~~~~~~~~~~~~~~
        
        Changed
        ^^^^^^^
        
        -  Change model downloading provider to cloudfront.
        
        .. _section-1:
        
        [0.7] - 2022-11-28
        ~~~~~~~~~~~~~~~~~~
        
        Added
        ^^^^^
        
        -  Add face swapping model and example.
        
        .. _changed-1:
        
        Changed
        ^^^^^^^
        
        -  Set default ORT provider to CUDA and CPU.
        
        .. _section-2:
        
        [0.6] - 2022-01-29
        ~~~~~~~~~~~~~~~~~~
        
        .. _added-1:
        
        Added
        ^^^^^
        
        -  Add pose estimation in face-analysis app.
        
        .. _changed-2:
        
        Changed
        ^^^^^^^
        
        -  Change model automated downloading url, to ucloud.
        
        Quick Example
        -------------
        
        ::
        
           import cv2
           import numpy as np
           import insightface
           from insightface.app import FaceAnalysis
           from insightface.data import get_image as ins_get_image
        
           app = FaceAnalysis(providers=['CUDAExecutionProvider', 'CPUExecutionProvider'])
           app.prepare(ctx_id=0, det_size=(640, 640))
           img = ins_get_image('t1')
           faces = app.get(img)
           rimg = app.draw_on(img, faces)
           cv2.imwrite("./t1_output.jpg", rimg)
        
        This quick example will detect faces from the ``t1.jpg`` image and draw
        detection results on it.
        
        Model Zoo
        ---------
        
        In the latest version of insightface library, we provide following model
        packs:
        
        Name in **bold** is the default model pack. **Auto** means we can
        download the model pack through the python library directly.
        
        Once you manually downloaded the zip model pack, unzip it under
        ``~/.insightface/models/`` first before you call the program.
        
        +-----+------+--------+----+---+---+---------------------------+-----+
        | Nam | Dete | Recogn | Al | A | M | Link                      | Aut |
        | e   | ctio | ition  | ig | t | o |                           | o   |
        |     | n    | Model  | nm | t | d |                           |     |
        |     | Mode |        | en | r | e |                           |     |
        |     | l    |        | t  | i | l |                           |     |
        |     |      |        |    | b | - |                           |     |
        |     |      |        |    | u | S |                           |     |
        |     |      |        |    | t | i |                           |     |
        |     |      |        |    | e | z |                           |     |
        |     |      |        |    | s | e |                           |     |
        +=====+======+========+====+===+===+===========================+=====+
        | ant | SCRF | ResNet | 2d | G | 4 | `link <https://drive.goog | N   |
        | elo | D-10 | 100@Gl | 10 | e | 0 | le.com/file/d/18wEUfMNohB |     |
        | pev | GF   | int360 | 6  | n | 7 | J4K3Ly5wpTejPfDzp-8fI8/vi |     |
        | 2   |      | K      | &  | d | M | ew?usp=sharing>`__        |     |
        |     |      |        | 3d | e | B |                           |     |
        |     |      |        | 68 | r |   |                           |     |
        |     |      |        |    | & |   |                           |     |
        |     |      |        |    | A |   |                           |     |
        |     |      |        |    | g |   |                           |     |
        |     |      |        |    | e |   |                           |     |
        +-----+------+--------+----+---+---+---------------------------+-----+
        | **b | SCRF | ResNet | 2d | G | 3 | `link <https://drive.goog | Y   |
        | uff | D-10 | 50@Web | 10 | e | 2 | le.com/file/d/1qXsQJ8ZT42 |     |
        | alo | GF   | Face60 | 6  | n | 6 | _xSmWIYy85IcidpiZudOCB/vi |     |
        | _l* |      | 0K     | &  | d | M | ew?usp=sharing>`__        |     |
        | *   |      |        | 3d | e | B |                           |     |
        |     |      |        | 68 | r |   |                           |     |
        |     |      |        |    | & |   |                           |     |
        |     |      |        |    | A |   |                           |     |
        |     |      |        |    | g |   |                           |     |
        |     |      |        |    | e |   |                           |     |
        +-----+------+--------+----+---+---+---------------------------+-----+
        | buf | SCRF | ResNet | 2d | G | 3 | `link <https://drive.goog | N   |
        | fal | D-2. | 50@Web | 10 | e | 1 | le.com/file/d/1net68yNxF3 |     |
        | o_m | 5GF  | Face60 | 6  | n | 3 | 3NNV6WP7k56FS6V53tq-64/vi |     |
        |     |      | 0K     | &  | d | M | ew?usp=sharing>`__        |     |
        |     |      |        | 3d | e | B |                           |     |
        |     |      |        | 68 | r |   |                           |     |
        |     |      |        |    | & |   |                           |     |
        |     |      |        |    | A |   |                           |     |
        |     |      |        |    | g |   |                           |     |
        |     |      |        |    | e |   |                           |     |
        +-----+------+--------+----+---+---+---------------------------+-----+
        | buf | SCRF | MBF@We | 2d | G | 1 | `link <https://drive.goog | N   |
        | fal | D-50 | bFace6 | 10 | e | 5 | le.com/file/d/1pKIusApEfo |     |
        | o_s | 0MF  | 00K    | 6  | n | 9 | HKDjeBTXYB3yOQ0EtTonNE/vi |     |
        |     |      |        | &  | d | M | ew?usp=sharing>`__        |     |
        |     |      |        | 3d | e | B |                           |     |
        |     |      |        | 68 | r |   |                           |     |
        |     |      |        |    | & |   |                           |     |
        |     |      |        |    | A |   |                           |     |
        |     |      |        |    | g |   |                           |     |
        |     |      |        |    | e |   |                           |     |
        +-----+------+--------+----+---+---+---------------------------+-----+
        | buf | SCRF | MBF@We | -  | - | 1 | `link <https://drive.goog | N   |
        | fal | D-50 | bFace6 |    |   | 6 | le.com/file/d/19I-MZdctYK |     |
        | o_s | 0MF  | 00K    |    |   | M | mVf3nu5Da3HS6KH5LBfdzG/vi |     |
        | c   |      |        |    |   | B | ew?usp=sharing>`__        |     |
        +-----+------+--------+----+---+---+---------------------------+-----+
        
        Recognition Accuracy:
        
        +-------+----+-----+-------+--------+--------+---+----+------+-------+
        | Name  | MR | Afr | Cauca | South  | East   | L | CF | AgeD | IJB-C |
        |       | -A | ica | sian  | Asian  | Asian  | F | P- | B-30 | (E4)  |
        |       | LL | n   |       |        |        | W | FP |      |       |
        +=======+====+=====+=======+========+========+===+====+======+=======+
        | buffa | 91 | 90. | 94.70 | 93.16  | 74.96  | 9 | 99 | 98.2 | 97.25 |
        | lo_l  | .2 | 29  |       |        |        | 9 | .3 | 3    |       |
        |       | 5  |     |       |        |        | . | 3  |      |       |
        |       |    |     |       |        |        | 8 |    |      |       |
        |       |    |     |       |        |        | 3 |    |      |       |
        +-------+----+-----+-------+--------+--------+---+----+------+-------+
        | buffa | 71 | 69. | 80.45 | 73.39  | 51.03  | 9 | 98 | 96.5 | 95.02 |
        | lo_s  | .8 | 45  |       |        |        | 9 | .0 | 8    |       |
        |       | 7  |     |       |        |        | . | 0  |      |       |
        |       |    |     |       |        |        | 7 |    |      |       |
        |       |    |     |       |        |        | 0 |    |      |       |
        +-------+----+-----+-------+--------+--------+---+----+------+-------+
        
        *buffalo_m has the same accuracy with buffalo_l.*
        
        *buffalo_sc has the same accuracy with buffalo_s.*
        
        **Note that these models are available for non-commercial research
        purposes only.**
        
        For insightface>=0.3.3, models will be downloaded automatically once we
        init ``app = FaceAnalysis()`` instance.
        
        For insightface==0.3.2, you must first download the model package by
        command:
        
        ::
        
           insightface-cli model.download buffalo_l
        
        Use Your Own Licensed Model
        ---------------------------
        
        You can simply create a new model directory under
        ``~/.insightface/models/`` and replace the pretrained models we provide
        with your own models. And then call
        ``app = FaceAnalysis(name='your_model_zoo')`` to load these models.
        
        Call Models
        -----------
        
        The latest insightface libary only supports onnx models. Once you have
        trained detection or recognition models by PyTorch, MXNet or any other
        frameworks, you can convert it to the onnx format and then they can be
        called with insightface library.
        
        Call Detection Models
        ~~~~~~~~~~~~~~~~~~~~~
        
        ::
        
           import cv2
           import numpy as np
           import insightface
           from insightface.app import FaceAnalysis
           from insightface.data import get_image as ins_get_image
        
           # Method-1, use FaceAnalysis
           app = FaceAnalysis(allowed_modules=['detection']) # enable detection model only
           app.prepare(ctx_id=0, det_size=(640, 640))
        
           # Method-2, load model directly
           detector = insightface.model_zoo.get_model('your_detection_model.onnx')
           detector.prepare(ctx_id=0, input_size=(640, 640))
        
        Call Recognition Models
        ~~~~~~~~~~~~~~~~~~~~~~~
        
        ::
        
           import cv2
           import numpy as np
           import insightface
           from insightface.app import FaceAnalysis
           from insightface.data import get_image as ins_get_image
        
           handler = insightface.model_zoo.get_model('your_recognition_model.onnx')
           handler.prepare(ctx_id=0)
        
        
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